What you have to remember when using the argument that young kids may be uncooperative/distractible/tired etc. is that all these conditions applied to the norming sample, too. If you take a sample now of kids testing, their scores will be "inflated" if they are on average less uncooperative etc. than the norming sample, "deflated" if they are more so. There's no reason that I can see to expect children being tested now to be *more* subject to those factors that might reduce their scores than the norming sample were, and therefore no reason to expect their scores to be underestimates as a group.
Yes - I think I agree, which was my earlier point about the norming sample possibly not being terribly valid because these would be issues all younger kids have that would mean the scores would potentially not be very stable in general.
If we dispose of that set of arguments on those grounds, then what remains is the regression to the mean argument.
What an individual tester sees is going, of course, to be heavily dependent on which children come to that tester to be tested. That could be affected by a lot of different things. For example, a tester who draws testees from a population where high IQs are the norm and only a really exceptional child is likely to be brought for testing (or one, like Miraca Gross, famous for being interested in PG children) is more likely to experience that scores tend to be underestimates than a tester who tests from a more average population.
But this seems to go against what others have said, which is that very high scores in young kids are likely to be very unstable? (Sorry, I can imagine better informed people reading my questions and thinking "what's not to get??") I also had the same thoughts as Mumofthree earlier today - I can see how regression to the mean would work on something like multiple choice, but from what I understand don't you pretty much have to earn your answer in an IQ test?
